The present invention relates to digital video signal processing, and more particularly to architectures and methods for digital camera red-eye processing.
Imaging and video capabilities have become the trend in consumer electronics. Digital cameras, digital camcorders, and video cellular phones are common, and many other new gadgets are evolving in the market. Advances in large resolution CCD/CMOS sensors coupled with the availability of low-power digital signal processors (DSPs) has led to the development of digital cameras with both high resolution image and short audio/visual clip capabilities. The high resolution (e.g., sensor with a 2560×1920 pixel array) provides quality offered by traditional film cameras.
FIG. 7 is a typical functional block diagram for digital camera control and image processing (the “image pipeline”). The automatic focus, automatic exposure, and automatic white balancing are referred to as the 3A functions; and the image processing includes functions such as color filter array (CFA) interpolation, gamma correction, white balancing, color space conversion, and JPEG/MPEG compression/decompression (JPEG for single images and MPEG for video clips). Note that the typical color CCD consists of a rectangular array of photosites (pixels) with each photosite covered by a filter (the CFA): typically, red, green, or blue. In the commonly-used Bayer pattern CFA one-half of the photosites are green, one-quarter are red, and one-quarter are blue.
Typical digital cameras provide a capture mode with full resolution image or audio/visual clip processing plus compression and storage, a preview mode with lower resolution processing for immediate display, and a playback mode for displaying stored images or audio/visual clips.
Capture of an image including one or more human faces while using flash illumination of the scene frequently leads to the problem of “redeye”: an artificial red appears around the pupils of the eyes in the faces. The red seems to be a reflection of the flash light from the blood vessels of the retinas in the eyes. Images of pets under flash illumination have a similar problem, the main difference being that the artificial color around the pupils varies (blue, green, yellow, et cetera).
Redeye is an objectionable artifact. There are currently three basic types of techniques for redeye mitigation and removal:                Redeye reduction: This technique is widely supported in current cameras. In this technique, one or more pre-exposure flashes are used to contract the pupil aperture, thereby reducing the probability of reflection of flash light from the retina. This technique consumes a lot of power and also involves a delay. This technique will not work if the subject is not looking at the camera during the pre-exposure flashes. Hence it is desirable to have an image processing approach wherein redeyes are removed in the captured image.        Semi-automatic techniques for redeye removal using image processing: In these techniques, the redeyes are removed from pictures by using image processing software typically running on a desktop computer. The user typically selects the region of redeyes in the redeye pictures. The redeyes are then removed by reducing or eliminating the chrominance information in the regions of selected redeyes.        Automatic redeye removal: In these techniques the redeye regions of the pictures are automatically detected and corrected. Automatic redeye removal is a new feature that is being introduced in digital still cameras; e.g., HP R707 and Nikon Coolpix 5200.        
FIG. 8 illustrates a common automatic approach as described in Gaubatz et al., Automatic Red-Eye Detection and Correction, Proc. IEEE Intl. Conf. Image Processing I-804 (2002) which first detects faces in an image, then detects red eyes within the faces, and lastly corrects red-eye by desaturating the red pixels. U.S. Pat. Nos. 6,718,051 and 6,728,401 are similar.